The present invention relates to computer model weather forecasts, and more specifically, to correcting computer model weather forecasts using a hybrid analog method with dynamic time warping.
Weather forecasting is the application of science and technology to predict the state of the atmosphere for a given location. Human beings have attempted to predict the weather informally for millennia, and formally since the nineteenth century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere at a given place and using scientific understanding of atmospheric processes to project how the atmosphere will change.
Once an all-human endeavor based mainly upon changes in barometric pressure, current weather conditions, and sky condition, weather forecasting now relies on computer-based models that take many atmospheric factors into account. Human input is still required to pick the best possible forecast model to base the forecast upon, which involves pattern recognition skills, teleconnections, knowledge of model performance, and knowledge of model biases. The inaccuracy of forecasting is due to the chaotic nature of the atmosphere, the massive computational power required to solve the equations that describe the atmosphere, the error involved in measuring the initial conditions, and an incomplete understanding of atmospheric processes. Hence, forecasts become less accurate as the difference between current time and the time for which the forecast is being made (the range of the forecast) increases. The use of ensembles and model consensus help narrow the error and pick the most likely outcome.
When forecasting weather events from computer models, time series data is one way of representing the forecasted parameter, or feature, over time. However, computer models often have bias or do not fit observations. Some models get the magnitude of the events correct but they may be temporally off, for instance predicting the right amount of rain but not in the appropriate time window (perhaps predicting a storm will move in later or earlier than it actually does).